Convergent network effects along the axis of gene expression during prostate cancer progression
Abstract Background Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. Results Here, we...
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2020-12-01
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Online Access: | https://doi.org/10.1186/s13059-020-02188-9 |
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language |
English |
format |
Article |
sources |
DOAJ |
author |
Konstantina Charmpi Tiannan Guo Qing Zhong Ulrich Wagner Rui Sun Nora C. Toussaint Christine E. Fritz Chunhui Yuan Hao Chen Niels J. Rupp Ailsa Christiansen Dorothea Rutishauser Jan H. Rüschoff Christian Fankhauser Karim Saba Cedric Poyet Thomas Hermanns Kathrin Oehl Ariane L. Moore Christian Beisel Laurence Calzone Loredana Martignetti Qiushi Zhang Yi Zhu María Rodríguez Martínez Matteo Manica Michael C. Haffner Ruedi Aebersold Peter J. Wild Andreas Beyer |
spellingShingle |
Konstantina Charmpi Tiannan Guo Qing Zhong Ulrich Wagner Rui Sun Nora C. Toussaint Christine E. Fritz Chunhui Yuan Hao Chen Niels J. Rupp Ailsa Christiansen Dorothea Rutishauser Jan H. Rüschoff Christian Fankhauser Karim Saba Cedric Poyet Thomas Hermanns Kathrin Oehl Ariane L. Moore Christian Beisel Laurence Calzone Loredana Martignetti Qiushi Zhang Yi Zhu María Rodríguez Martínez Matteo Manica Michael C. Haffner Ruedi Aebersold Peter J. Wild Andreas Beyer Convergent network effects along the axis of gene expression during prostate cancer progression Genome Biology Molecular aberrations Network effects Prostate cancer Proteogenomic analysis Tumor heterogeneity |
author_facet |
Konstantina Charmpi Tiannan Guo Qing Zhong Ulrich Wagner Rui Sun Nora C. Toussaint Christine E. Fritz Chunhui Yuan Hao Chen Niels J. Rupp Ailsa Christiansen Dorothea Rutishauser Jan H. Rüschoff Christian Fankhauser Karim Saba Cedric Poyet Thomas Hermanns Kathrin Oehl Ariane L. Moore Christian Beisel Laurence Calzone Loredana Martignetti Qiushi Zhang Yi Zhu María Rodríguez Martínez Matteo Manica Michael C. Haffner Ruedi Aebersold Peter J. Wild Andreas Beyer |
author_sort |
Konstantina Charmpi |
title |
Convergent network effects along the axis of gene expression during prostate cancer progression |
title_short |
Convergent network effects along the axis of gene expression during prostate cancer progression |
title_full |
Convergent network effects along the axis of gene expression during prostate cancer progression |
title_fullStr |
Convergent network effects along the axis of gene expression during prostate cancer progression |
title_full_unstemmed |
Convergent network effects along the axis of gene expression during prostate cancer progression |
title_sort |
convergent network effects along the axis of gene expression during prostate cancer progression |
publisher |
BMC |
series |
Genome Biology |
issn |
1474-760X |
publishDate |
2020-12-01 |
description |
Abstract Background Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. Results Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. Conclusions This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions. |
topic |
Molecular aberrations Network effects Prostate cancer Proteogenomic analysis Tumor heterogeneity |
url |
https://doi.org/10.1186/s13059-020-02188-9 |
work_keys_str_mv |
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doaj-707dce3d6d5841db93fe381dce66b0c02020-12-20T12:39:44ZengBMCGenome Biology1474-760X2020-12-0121113110.1186/s13059-020-02188-9Convergent network effects along the axis of gene expression during prostate cancer progressionKonstantina Charmpi0Tiannan Guo1Qing Zhong2Ulrich Wagner3Rui Sun4Nora C. Toussaint5Christine E. Fritz6Chunhui Yuan7Hao Chen8Niels J. Rupp9Ailsa Christiansen10Dorothea Rutishauser11Jan H. Rüschoff12Christian Fankhauser13Karim Saba14Cedric Poyet15Thomas Hermanns16Kathrin Oehl17Ariane L. Moore18Christian Beisel19Laurence Calzone20Loredana Martignetti21Qiushi Zhang22Yi Zhu23María Rodríguez Martínez24Matteo Manica25Michael C. Haffner26Ruedi Aebersold27Peter J. Wild28Andreas Beyer29CECAD, University of CologneDepartment of Biology, Institute of Molecular Systems Biology, ETH ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake UniversityDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake UniversityZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake UniversityDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Urology, University Hospital Zurich, University of ZurichDepartment of Urology, University Hospital Zurich, University of ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichDepartment of Biosystems Science and Engineering, ETH ZurichDepartment of Biosystems Science and Engineering, ETH ZurichInstitut CurieInstitut CurieZhejiang Provincial Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake UniversityDepartment of Biology, Institute of Molecular Systems Biology, ETH ZurichIBM Zurich Research LaboratoryIBM Zurich Research LaboratoryFred Hutchinson Cancer Research CenterDepartment of Biology, Institute of Molecular Systems Biology, ETH ZurichDepartment of Pathology and Molecular Pathology, University Hospital Zurich, University of ZurichCECAD, University of CologneAbstract Background Tumor-specific genomic aberrations are routinely determined by high-throughput genomic measurements. It remains unclear how complex genome alterations affect molecular networks through changing protein levels and consequently biochemical states of tumor tissues. Results Here, we investigate the propagation of genomic effects along the axis of gene expression during prostate cancer progression. We quantify genomic, transcriptomic, and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis reveals the convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devise a network-based approach that integrates perturbations across different molecular layers, which identifies a sub-network consisting of nine genes whose joint activity positively correlates with increasingly aggressive tumor phenotypes and is predictive of recurrence-free survival. Further, our data reveal a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. Conclusions This study uncovers molecular networks with considerable convergent alterations across tumor sites and patients. It also exposes a diversity of network effects: we could not identify a single sub-network that is perturbed in all high-grade tumor regions.https://doi.org/10.1186/s13059-020-02188-9Molecular aberrationsNetwork effectsProstate cancerProteogenomic analysisTumor heterogeneity |